“highly significant”

The frequencies of white choices in S1 and S2 showed a highly significant difference between sessions (χ 2 = 272.23, P <0.00001).

The F-ratio comparing the variances across time was highly significant (F 479,479 = 14.5144, P < 0.00001).

These differences were highly significant (P < 0.00001).

With 10, 000 random permutation test, we confirmed such an enrichment of genes with higher expression variability in YRI is highly significant (P<10 −5 ).

For all data sets (cortical CBF, subcortical CBF or RBF; during blood removal or reperfusion), three-parameter logistic regression curves with highly significant correlations for blood flow and MABP could be fitted to the data ( Figure 4 ; correlation coefficients are given in the respective panels; p < 0.00001 for all data sets).

This difference was statistically highly significant (inpatient services: χ 2 = 113.257, P < 0.00001*; and outpatient services: χ 2 = 34.662, P < 0.00001*).

These models showed that indeed there are highly significant differences ( p < 0.00001) in infection rates between some populations for all three pathogens tested ( Data S2 ).

Hypergeometric tests showed a highly significant overrepresentation of genes of the non-normalized modules in each normalized module (P<0.00001) consistent with similar networks being recovered by the two approaches.

Predictive Value of the First Injection on Long-Term Outcome There was a highly significant (r = 0.855, p < 0.00001) correlation between the outcome 30 days after the first injection and the outcome after one year of continuous 3-monthly injection therapy for the pRoMs ( Figure 3 A).

The LSL model ( Table 1 ) returned highly significant effects ( p < 0.00001) for both ES Yield and Yield Control .

5 showed a highly significant difference for these pairs of groups, p < 0.00001.

Using multivariate analysis of variance (MANOVA), the difference in the consumption frequencies of the items was highly significant ( p -value = 0.00001).

Here, we detected a total of six highly significant association signals ( p < 1 × 10 −5 ) for i-LT, corresponding to five unique genes, consistent with a previous report ( Supplemental Table 7 ) ( Wei et al., 2018 ) and suggesting the potential importance of these candidate genes for final PH in maize.

Principal component analysis (PCA) further confirmed distinct microbial community structures between groups, The PERMANOVA analysis revealed a highly significant difference between the two groups ( p = 0.00001) ( Fig. 1C ).

Correlation analysis between the co-expression module and traits was carried out, and two highly significant trait-related modules (|cor| > 0.75, p -value < 1 × 10 −5 ) were identified.

Between the Non-Gly and the Gly subtypes, we identified 763 highly significant Differentially Expressed (DE) genes (Adj. p < 1E-05), 296 of which over-expressed in Gly subtype and 466 over-expressed in the Non-Gly tumors ( Figure 2A and Supplementary Table 3 ).

Prevalence of SNOCIs who presented with solitary positive anti-HCV IgG antibody in non-viremia patients (34.82%) was highly significant (higher) compared to prevalence of COCIs (3.125%) in negative controls for both IgG antibodies and viremia ( p < 0.00001).

The overall effect was highly significant (Z = 7.70, p < 0.00001), further supporting the effectiveness of this dosage.

The overall effect was also highly significant (Z = 5.20, P < 0.00001) (Fig. 4 b).

The difference in classification performance between sexes was highly significant (Mann–Whitney U‐test, p < 0.00001, Figure 4A , effect size d = 0.8), showing a strong sex‐related bias in models trained without using ERP features.

This was highly significant ( p < 0.00001) ( Table 2 ).

The standard post-operative treatment in most early trials was CMF polychemotherapy (cyclophosphamide, methotrexate, and 5-fluorouracil), but recent evidence suggests that there is a small but highly significant further survival benefit with anthracycline-based regimens (RR=0.89; 2 P <0.00001) ( EBCTCG, 2005 ), and these have become widely accepted as standard adjuvant chemotherapy.

Microbial composition was compared across samples using Bray–Curtis dissimilarity, demonstrating a highly significant difference ( p < 10 −5 ) between feces and tissue ( Figure 1 A).

6b and 6f ) is highly significant ( p = 10 −5 ).

A linear regression model between vehicle occupants’ death rate and seatbelt noncompliance in our published data was highly significant ( P <.00001) ( Figure 1 ).